Warning: This analysis contains the results of a predictive model. There are a number of assumptions made which include some speculation. Furthermore, this analysis was not prepared or reviewed by an epidemiologist. Therefore, the assumptions and methods presented should be scrutinized carefully before arriving at any conclusions.

Based on data up to: 2020-04-17

Projected need for ICU beds

Countries sorted by current ICU demand

  • ICU need is estimated as 4.4% of active reported cases.- ICU capacities are from Wikipedia (OECD countries mostly) and CCB capacities in Asia.
  • ICU spare capacity is based on 70% normal occupancy rate (66% in US, 75% OECD)

  • Details of estimation and prediction calculations are in Appendix, as well as Plots of model predictions.

  • Column definitions:

    • Estimated ICU need per 100k population: number of ICU beds estimated to be needed per 100k population by COVID-19 patents.
    • Estimated daily case growth rate: percentage daily change in total cases during last 5 days.
    • Projected ICU need per 100k in 14 days: self explanatory.
    • Projected ICU need per 100k in 30 days: self explanatory.
    • ICU capacity per 100k: number of ICU beds per 100k population.
    • Estimated ICU Spare capacity per 100k: estimated ICU capacity per 100k population based on assumed normal occupancy rate of 70% and number of ICU beds (only for countries with ICU beds data).

Tip: The red (need for ICU) and the blue (ICU spare capacity) bars are on the same 0-10 scale, for easy visual comparison of columns.
Estimated
current
ICU need
per 100k
population		 Estimated
daily case
growth rate		 Projected
ICU need
per 100k
In 14 days		 Projected
ICU need
per 100k
In 30 days		 ICU
capacity
per 100k		 Estimated ICU
Spare capacity
per 100k
Country/Region
Spain 10.57 2.8% ± 0.9% 10.1 ± 2.3 9.5 ± 4.6 9.7 2.9
Ireland 10.52 7.5% ± 1.9% 19.5 ± 7.6 noisy data 6.5 1.9
Belgium 9.60 4.1% ± 2.0% 10.7 ± 4.4 noisy data 15.9 4.8
France 7.27 noisy data noisy data noisy data 11.6 3.5
US 7.00 4.7% ± 0.1% 8.4 ± 0.2 10.3 ± 0.5 34.7 10.4
Switzerland 6.77 1.3% ± 0.2% 4.9 ± 0.3 3.3 ± 0.5 11.0 3.3
Italy 6.20 2.0% ± 0.2% 5.4 ± 0.3 4.6 ± 0.6 12.5 3.8
United Kingdom 5.56 5.2% ± 0.4% 7.0 ± 0.5 9.0 ± 1.4 6.6 2.0
Portugal 5.46 2.8% ± 1.2% 4.9 ± 1.2 noisy data 4.2 1.3
Netherlands 5.16 3.5% ± 0.5% 5.4 ± 0.6 5.8 ± 1.4 6.4 1.9
Israel 4.25 3.1% ± 1.0% 4.1 ± 0.9 4.0 ± 1.9 - -
Germany 4.22 2.1% ± 0.6% 3.5 ± 0.5 2.8 ± 0.9 29.2 8.8
Sweden 4.04 4.8% ± 0.5% 5.2 ± 0.5 6.9 ± 1.3 5.8 1.7
Singapore 3.66 15.0% ± 2.8% 24.8 ± 11.2 noisy data 11.4 3.4
Turkey 3.50 6.6% ± 0.5% 5.2 ± 0.4 8.4 ± 1.3 47.1 14.1
Denmark 3.36 2.7% ± 0.2% 3.1 ± 0.2 2.8 ± 0.3 6.7 2.0
Austria 3.28 0.9% ± 0.2% 2.2 ± 0.1 1.3 ± 0.2 21.8 6.5
Panama 3.10 4.5% ± 1.8% 3.5 ± 1.2 noisy data - -
Canada 2.97 6.3% ± 1.7% 4.6 ± 1.6 noisy data 13.5 4.0
Estonia 2.65 2.2% ± 0.5% 2.3 ± 0.3 2.0 ± 0.5 14.6 4.4
UAE 2.55 8.8% ± 0.5% 5.5 ± 0.5 13.8 ± 3.1 - -
Serbia 2.53 9.2% ± 1.5% 6.3 ± 1.9 noisy data - -
Norway 2.50 noisy data 1.9 ± 0.4 noisy data 8.0 2.4
Belarus 2.33 13.2% ± 0.5% 9.2 ± 0.7 48.4 ± 8.3 - -
Iran 2.17 2.1% ± 0.1% 1.9 ± 0.1 1.6 ± 0.1 4.6 1.4
Moldova 2.06 noisy data noisy data noisy data - -
Cyprus 1.82 3.4% ± 1.1% 1.8 ± 0.4 noisy data - -
Peru 1.80 noisy data noisy data noisy data - -
North Macedonia 1.80 6.3% ± 2.9% noisy data noisy data - -
Finland 1.80 3.3% ± 0.6% 1.8 ± 0.2 1.8 ± 0.5 6.1 1.8
Chile 1.59 5.1% ± 0.8% 2.1 ± 0.3 2.8 ± 0.9 - -
Ecuador 1.57 noisy data 1.3 ± 0.4 noisy data - -
Czechia 1.54 noisy data 1.2 ± 0.3 0.9 ± 0.4 11.6 3.5
Romania 1.39 5.1% ± 1.0% 1.8 ± 0.3 2.4 ± 1.0 - -
Dominican Republic 1.35 7.0% ± 2.8% noisy data noisy data - -
Slovenia 1.35 noisy data 1.1 ± 0.3 noisy data 6.4 1.9
Croatia 1.18 2.5% ± 0.7% 1.1 ± 0.2 0.9 ± 0.3 - -
Bosnia 1.14 3.8% ± 1.0% 1.2 ± 0.2 1.3 ± 0.6 - -
Armenia 1.11 3.5% ± 0.7% 1.2 ± 0.2 1.3 ± 0.5 - -
Lithuania 1.10 noisy data 0.8 ± 0.2 noisy data 15.5 4.6
Russia 1.00 15.1% ± 0.8% 5.6 ± 0.7 46.2 ± 12.8 8.3 2.5
Saudi Arabia 0.79 9.9% ± 1.3% 2.4 ± 0.6 noisy data 22.8 6.8
New Zealand 0.75 1.2% ± 0.3% 0.5 ± 0.0 0.3 ± 0.1 - -
Poland 0.72 4.7% ± 0.8% 0.9 ± 0.1 1.1 ± 0.3 6.9 2.1
Hungary 0.62 4.6% ± 1.2% 0.7 ± 0.2 0.9 ± 0.4 13.8 4.1
Brazil 0.61 8.9% ± 2.3% 1.4 ± 0.7 noisy data - -
Albania 0.51 3.9% ± 1.1% 0.6 ± 0.2 noisy data - -
Australia 0.51 0.6% ± 0.3% 0.3 ± 0.0 0.2 ± 0.0 9.1 2.7
Greece 0.46 1.0% ± 0.3% 0.3 ± 0.0 0.2 ± 0.0 6.0 1.8
Azerbaijan 0.45 4.1% ± 0.9% 0.5 ± 0.1 0.5 ± 0.2 - -
Ukraine 0.44 11.0% ± 1.2% 1.4 ± 0.3 6.0 ± 2.9 - -
Malaysia 0.40 2.3% ± 0.8% 0.4 ± 0.1 0.3 ± 0.1 3.4 1.0
Bulgaria 0.34 4.7% ± 1.8% 0.5 ± 0.2 noisy data - -
Kazakhstan 0.31 10.1% ± 3.3% noisy data noisy data 21.3 6.4
Cuba 0.30 6.6% ± 1.0% 0.5 ± 0.1 0.8 ± 0.3 - -
Japan 0.29 8.0% ± 3.5% noisy data noisy data 7.3 2.2
Morocco 0.26 9.5% ± 2.9% noisy data noisy data - -
Colombia 0.23 4.4% ± 1.2% 0.3 ± 0.1 0.3 ± 0.1 - -
Tunisia 0.21 4.2% ± 1.1% 0.3 ± 0.1 noisy data - -
Lebanon 0.19 noisy data 0.1 ± 0.0 noisy data - -
Mexico 0.19 8.3% ± 1.0% 0.4 ± 0.1 0.9 ± 0.4 1.2 0.4
Argentina 0.18 4.5% ± 1.6% 0.2 ± 0.1 noisy data - -
Algeria 0.17 4.9% ± 1.0% 0.2 ± 0.0 0.3 ± 0.1 - -
Philippines 0.17 4.8% ± 1.0% 0.2 ± 0.0 0.3 ± 0.1 2.2 0.7
Bolivia 0.15 9.1% ± 2.6% noisy data noisy data - -
South Korea 0.15 0.2% ± 0.0% 0.1 ± 0.0 0.1 ± 0.0 10.6 3.2
South Africa 0.13 5.1% ± 1.3% 0.2 ± 0.1 noisy data - -
Honduras 0.13 2.4% ± 1.0% 0.1 ± 0.0 0.1 ± 0.0 - -
Cameroon 0.12 noisy data noisy data noisy data - -
Pakistan 0.11 6.1% ± 2.8% noisy data noisy data 1.5 0.4
Niger 0.10 noisy data noisy data noisy data - -
Iraq 0.10 1.9% ± 0.8% 0.1 ± 0.0 0.1 ± 0.0 - -
Egypt 0.10 6.6% ± 0.4% 0.2 ± 0.0 0.3 ± 0.0 - -
Afghanistan 0.09 8.3% ± 1.1% 0.2 ± 0.0 noisy data - -
Thailand 0.09 1.1% ± 0.1% 0.1 ± 0.0 0.0 ± 0.0 10.4 3.1
Indonesia 0.08 6.9% ± 0.6% 0.1 ± 0.0 0.2 ± 0.1 2.7 0.8
Burkina Faso 0.07 noisy data 0.1 ± 0.0 noisy data - -
Bangladesh 0.06 23.4% ± 4.7% noisy data noisy data 0.7 0.2
India 0.04 9.1% ± 2.3% 0.1 ± 0.0 noisy data 5.2 1.6
Mali 0.03 noisy data noisy data noisy data - -
Kenya 0.01 4.5% ± 0.7% 0.0 ± 0.0 0.0 ± 0.0 - -
China 0.01 noisy data noisy data noisy data 3.6 1.1
Nigeria 0.01 9.0% ± 1.7% 0.0 ± 0.0 noisy data - -

Appendix

Interactive plot of Model predictions

Tip: Choose a country from the drop-down menu to see the calculations used in the tables above and the dynamics of the model.

Projected Affected Population percentage

Countries sorted by number of new cases in last 5 days. The projected affected population percentage is directly related to the calculation of estimated ICU need.

  • Column definitions:
    • Estimated new cases in last 5 days: self explanatory.
    • Estimated total affected population percentage: estimated percentage of total population already affected (infected, recovered, or dead).
    • Estimated daily case growth rate: percentage daily change in total cases during last 5 days.
    • Projected total affected percentage in 14 days: of population.
    • Projected total affected percentage in 30 days: of population.
    • Reported fatality percentage: reported total deaths divided by total cases.
Estimated
new cases
in last
5 days		 Estimated
total
affected
population
percentage		 Estimated
daily case
growth rate		 Projected
total
affected
percentage
In 14 days		 Projected
total
affected
percentage
In 30 days		 Reported
fatality
percentage
Country/Region
US 500,318 0.8% 4.7% ± 0.1% 1.3% ± 0.0% 2.0% ± 0.1% 5.3%
France 255,208 2.2% noisy data 3.5% ± 1.3% noisy data 12.5%
United Kingdom 236,830 1.6% 5.2% ± 0.4% 2.8% ± 0.1% 4.7% ± 0.5% 13.3%
Spain 136,270 2.4% 2.8% ± 0.9% 3.2% ± 0.4% 4.1% ± 1.0% 10.5%
Italy 110,658 2.0% 2.0% ± 0.2% 2.5% ± 0.1% 3.0% ± 0.2% 13.2%
Brazil 59,143 0.1% 8.9% ± 2.3% 0.2% ± 0.1% noisy data 6.4%
Belgium 58,332 2.9% 4.1% ± 2.0% 4.5% ± 1.2% noisy data 14.3%
Turkey 39,295 0.2% 6.6% ± 0.5% 0.4% ± 0.0% 0.7% ± 0.1% 2.3%
Netherlands 33,583 1.3% 3.5% ± 0.5% 1.9% ± 0.1% 2.6% ± 0.4% 11.3%
Iran 25,422 0.3% 2.1% ± 0.1% 0.4% ± 0.0% 0.5% ± 0.0% 6.2%
Canada 24,287 0.3% 6.3% ± 1.7% 0.5% ± 0.1% noisy data 4.1%
Germany 21,688 0.3% 2.1% ± 0.6% 0.3% ± 0.0% 0.4% ± 0.1% 3.1%
Russia 19,092 0.0% 15.1% ± 0.8% 0.2% ± 0.0% 1.4% ± 0.4% 0.9%
Sweden 18,210 0.9% 4.8% ± 0.5% 1.5% ± 0.1% 2.5% ± 0.3% 10.6%
India 16,203 0.0% 9.1% ± 2.3% 0.0% ± 0.0% noisy data 3.4%
Ireland 15,186 1.1% 7.5% ± 1.9% 2.5% ± 0.7% noisy data 3.8%
Peru 14,862 0.1% noisy data noisy data noisy data 2.2%
Mexico 13,828 0.0% 8.3% ± 1.0% 0.1% ± 0.0% 0.2% ± 0.1% 7.7%
Bangladesh 12,149 0.0% 23.4% ± 4.7% noisy data noisy data 4.1%
Indonesia 11,567 0.0% 6.9% ± 0.6% 0.0% ± 0.0% 0.1% ± 0.0% 8.8%
Romania 6,083 0.2% 5.1% ± 1.0% 0.3% ± 0.0% 0.4% ± 0.1% 5.1%
Ukraine 5,455 0.0% 11.0% ± 1.2% 0.1% ± 0.0% 0.5% ± 0.2% 2.7%
Japan 5,406 0.0% 8.0% ± 3.5% noisy data noisy data 1.9%
Philippines 5,089 0.0% 4.8% ± 1.0% 0.0% ± 0.0% 0.1% ± 0.0% 6.6%
Portugal 4,995 0.4% 2.8% ± 1.2% 0.5% ± 0.1% 0.7% ± 0.2% 3.5%
Algeria 4,798 0.1% 4.9% ± 1.0% 0.1% ± 0.0% 0.2% ± 0.0% 15.1%
Poland 4,427 0.1% 4.7% ± 0.8% 0.1% ± 0.0% 0.2% ± 0.0% 4.0%
Dominican Republic 4,310 0.2% 7.0% ± 2.8% 0.3% ± 0.1% noisy data 4.8%
Egypt 4,104 0.0% 6.6% ± 0.4% 0.0% ± 0.0% 0.1% ± 0.0% 7.2%
Switzerland 3,992 0.8% 1.3% ± 0.2% 0.9% ± 0.0% 1.0% ± 0.0% 4.9%
Morocco 3,883 0.0% 9.5% ± 2.9% 0.1% ± 0.0% noisy data 5.3%
Ecuador 3,636 0.2% noisy data 0.2% ± 0.0% 0.3% ± 0.1% 5.0%
Serbia 3,466 0.1% 9.2% ± 1.5% 0.3% ± 0.1% noisy data 1.9%
Saudi Arabia 3,119 0.0% 9.9% ± 1.3% 0.1% ± 0.0% 0.3% ± 0.2% 1.2%
Belarus 2,767 0.1% 13.2% ± 0.5% 0.3% ± 0.0% 1.8% ± 0.3% 0.9%
Singapore 2,518 0.1% 15.0% ± 2.8% 0.6% ± 0.3% noisy data 0.2%
Hungary 2,456 0.1% 4.6% ± 1.2% 0.2% ± 0.0% 0.3% ± 0.1% 8.8%
Pakistan 2,364 0.0% 6.1% ± 2.8% 0.0% ± 0.0% noisy data 1.9%
Denmark 2,259 0.3% 2.7% ± 0.2% 0.4% ± 0.0% 0.5% ± 0.0% 4.6%
UAE 2,179 0.1% 8.8% ± 0.5% 0.2% ± 0.0% 0.5% ± 0.1% 0.6%
Chile 2,039 0.1% 5.1% ± 0.8% 0.1% ± 0.0% 0.1% ± 0.0% 1.3%
Colombia 1,996 0.0% 4.4% ± 1.2% 0.0% ± 0.0% 0.1% ± 0.0% 4.4%
Israel 1,837 0.2% 3.1% ± 1.0% 0.2% ± 0.0% 0.3% ± 0.1% 1.2%
Argentina 1,582 0.0% 4.5% ± 1.6% 0.0% ± 0.0% 0.0% ± 0.0% 4.6%
China 1,523 0.0% noisy data 0.0% ± 0.0% 0.0% ± 0.0% 5.5%
Panama 1,479 0.2% 4.5% ± 1.8% 0.3% ± 0.1% 0.5% ± 0.2% 2.7%
Moldova 1,157 0.1% noisy data 0.2% ± 0.1% noisy data 2.5%
North Macedonia 946 0.2% 6.3% ± 2.9% 0.4% ± 0.2% noisy data 4.4%
Austria 922 0.2% 0.9% ± 0.2% 0.3% ± 0.0% 0.3% ± 0.0% 3.0%
Bolivia 866 0.0% 9.1% ± 2.6% 0.1% ± 0.0% noisy data 6.7%
Afghanistan 831 0.0% 8.3% ± 1.1% 0.0% ± 0.0% 0.1% ± 0.0% 3.3%
Czechia 758 0.1% noisy data 0.1% ± 0.0% 0.1% ± 0.0% 2.6%
Finland 713 0.1% 3.3% ± 0.6% 0.1% ± 0.0% 0.2% ± 0.0% 2.4%
South Africa 699 0.0% 5.1% ± 1.3% 0.0% ± 0.0% 0.0% ± 0.0% 1.8%
Cuba 685 0.0% 6.6% ± 1.0% 0.0% ± 0.0% 0.1% ± 0.0% 3.4%
Kazakhstan 595 0.0% 10.1% ± 3.3% 0.0% ± 0.0% noisy data 1.1%
Malaysia 568 0.0% 2.3% ± 0.8% 0.0% ± 0.0% 0.0% ± 0.0% 1.6%
Mali 536 0.0% noisy data noisy data noisy data 7.6%
Bulgaria 504 0.0% 4.7% ± 1.8% 0.1% ± 0.0% noisy data 4.8%
Bosnia 488 0.1% 3.8% ± 1.0% 0.1% ± 0.0% 0.2% ± 0.1% 3.8%
Norway 467 0.1% noisy data 0.2% ± 0.0% 0.2% ± 0.0% 2.3%
Nigeria 460 0.0% 9.0% ± 1.7% 0.0% ± 0.0% noisy data 3.4%
Tunisia 403 0.0% 4.2% ± 1.1% 0.0% ± 0.0% 0.0% ± 0.0% 4.3%
Iraq 376 0.0% 1.9% ± 0.8% 0.0% ± 0.0% 0.0% ± 0.0% 5.5%
Greece 267 0.1% 1.0% ± 0.3% 0.1% ± 0.0% 0.1% ± 0.0% 4.9%
Albania 266 0.1% 3.9% ± 1.1% 0.1% ± 0.0% 0.1% ± 0.0% 4.8%
Honduras 260 0.0% 2.4% ± 1.0% 0.0% ± 0.0% 0.0% ± 0.0% 9.3%
Slovenia 256 0.2% noisy data 0.2% ± 0.0% 0.2% ± 0.1% 5.1%
Croatia 245 0.1% 2.5% ± 0.7% 0.1% ± 0.0% 0.1% ± 0.0% 2.0%
Azerbaijan 242 0.0% 4.1% ± 0.9% 0.0% ± 0.0% 0.0% ± 0.0% 1.1%
Cameroon 241 0.0% noisy data noisy data noisy data 2.2%
Burkina Faso 212 0.0% noisy data 0.0% ± 0.0% noisy data 6.3%
Estonia 211 0.2% 2.2% ± 0.5% 0.2% ± 0.0% 0.2% ± 0.0% 2.6%
Australia 207 0.0% 0.6% ± 0.3% 0.0% ± 0.0% 0.0% ± 0.0% 1.0%
Niger 197 0.0% noisy data 0.0% ± 0.0% noisy data 2.9%
Armenia 188 0.0% 3.5% ± 0.7% 0.1% ± 0.0% 0.1% ± 0.0% 1.6%
Thailand 149 0.0% 1.1% ± 0.1% 0.0% ± 0.0% 0.0% ± 0.0% 1.7%
Lithuania 148 0.1% noisy data 0.1% ± 0.0% 0.1% ± 0.0% 2.9%
Kenya 138 0.0% 4.5% ± 0.7% 0.0% ± 0.0% 0.0% ± 0.0% 4.5%
South Korea 123 0.0% 0.2% ± 0.0% 0.0% ± 0.0% 0.0% ± 0.0% 2.2%
Cyprus 117 0.1% 3.4% ± 1.1% 0.1% ± 0.0% 0.1% ± 0.0% 1.6%
New Zealand 79 0.0% 1.2% ± 0.3% 0.0% ± 0.0% 0.0% ± 0.0% 0.8%
Lebanon 62 0.0% noisy data 0.0% ± 0.0% 0.0% ± 0.0% 3.1%

Methodology & Assumptions

  • I'm not an epidemiologist. This is an attempt to understand what's happening, and what the future looks like if current trends remain unchanged.
  • Everything is approximated and depends heavily on underlying assumptions.
  • Countries with less than 10 total deaths or less than 1 Million population are excluded.
  • Projection is done using a simple SIR model with (see examples) combined with the approach in Total Outstanding Cases:
    • Growth rate calculated over the 5 past days. This is pessimistic - because it includes the testing rate growth rate as well, and is slow to react to both improvements in test coverage and "flattening" due to social isolation.
    • Confidence bounds are calculated by from the weighted STD of the growth rate over the last 5 days. Model predictions are calculated for growth rates within 1 STD of the weighted mean. The maximum and minimum values for each day are used as confidence bands.
    • For projections (into future) very noisy projections (with broad confidence bounds) are not shown in the tables.
    • Recovery probability being 1/20 (for 20 days to recover) where the rate estimated from Total Outstanding Cases is too high (on down-slopes).
  • ICU need is calculated as being 4.4% of active reported cases where:
    • Active cases are taken from the SIR model. The ICU need is calculated from reported cases rather than from total estimated active cases. This is because the ICU ratio (4.4%) is based on symptomatic reported cases.
    • ICU capacities are from Wikipedia (OECD countries mostly) and CCB capacities in Asia.
    • ICU spare capacity is based on 70% normal occupancy rate (66% in US, 75% OECD)
  • Total case estimation calculated from deaths by:
    • Assuming that unbiased fatality rate is 2.3% (from heavily tested countries / the cruise ship data) and that it takes 8 days on average for a case to go from being confirmed positive (after incubation + testing lag) to death. This is the same figure used by "Estimating The Infected Population From Deaths".
    • Testing bias: the actual lagged fatality rate is than divided by the 2.3% figure to estimate the testing bias in a country. The estimated testing bias then multiplies the reported case numbers to estimate the true case numbers (=case numbers if testing coverage was as comprehensive as in the heavily tested countries).
    • The testing bias calculation is a high source of uncertainty in all these estimations and projections. Better source of testing bias (or just true case numbers), should make everything more accurate.